Les candidats postulant à un poste comme Software Engineer chez Amazon attribuent un niveau de difficulté de 3,5 sur 5 (5 étant le niveau de difficulté le plus élevé) à leur expérience d’entretien et sont 50 % à l’évaluer comme positive. À titre de comparaison, la moyenne pour l’ensemble de l’entreprise est de 70,8 % d’avis positifs, d’après les évaluations Glassdoor.
D’après 2 entretiens Glassdoor, les étapes typiques du processus d’entretien d’embauche pour un poste comme Software Engineer chez Amazon incluent :
Entretien téléphonique: 50 %
Test des compétences: 50 %
Voici les rôles les plus recherchés pour les rapports d’entretien -
I was first asked to solve a problem using binary search—the interviewer emphasized both correctness and efficiency, so I had to carefully reason through edge cases and optimize my implementation. After that, I tackled a heap-related question that involved designing a data structure to support dynamic retrieval of the top‑k elements. The focus was on choosing the right heap type (min-heap vs. max-heap), maintaining time complexity, and explaining trade-offs clearly. Throughout, the interviewer encouraged me to think out loud and discuss my approach, which helped make it a collaborative and engaging experience.
Questions d'entretien [1]
Question 1
Given an array nums, find a peak element and return its index.
You may assume that nums[i] ≠ nums[i + 1] for all valid i.
The array may contain multiple peaks—return the index of any one.
Interviewed for silicon team. Have only been asked about the domain specific knowledge in 1st round and system design in 2nd round and C coding in 3rd round.
The interviews were 50 mins each.
First round with hr screening - 2 leetcode questions then hr manager screening then the loop which consists of 4 interviews each an hour long. The 4 interview questions they asked where three medium leetcode questions. And one system design interview question about how to shadow deploy a test software to millions of users.
The phone screen went longer than expected, focusing heavily on implementation details. The interviewer really grilled me on my approach to a Least Recently Used (LRU) cache, asking how I'd combine a hashmap with a doubly linked list. I felt well-prepared since I had gone through system design examples on PracHub, which made me comfortable discussing eviction policies. The later rounds included more technical questions and behavioral interviews, but in the end, I received an offer, though I ultimately decided to decline. Overall, I’d say the process was average, with solid questions.
Questions d'entretien [1]
Question 1
Design and implement a Least Recently Used (LRU) cache supporting get(key) and put(key, value) in O(1) average time. Walk through combining a hashmap with a doubly linked list, eviction policy when capacity is exceeded, and how you'd extend it to handle thread-safe concurrent access.